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Simplify using Amazon Mechanical Turk in your applications with an API tailored to your programming language or platform.

Video Presentations

Harness the Power of Crowdsourcing with Amazon Mechanical Turk

In this talk, we cover key concepts for Mechanical Turk and share best practices for how to integrate and scale your crowdsourced application. By the end of this talk, expect to have a general understanding of Mechanical Turk and how to get started harnessing the power of the crowd. (55:02)

Humans vs. the Machines: How Pinterest Uses the Amazon Mechanical Turk Worker Community to Improve Machine Learning

In this video, we explore how Pinterest adapted to an increased reliability on human evaluation to improve their product, with a focus on how they’ve integrated with Amazon Mechanical Turk’s platform. The discussion focuses on the analysis and product decisions related to building a high quality crowdsourcing system that takes advantage of Amazon Mechanical Turk’s powerful worker community. (35:17)

Business Process Automation Using Crowdsourcing

In this talk, learn how enterprises are using Mechanical Turk to scale and automate their human-powered workflow. (1:01:53)

Training Chatbots and Conversational Intelligence Agents with Amazon Mechanical Turk and Facebook's ParlAI

DigitalGlobe | Radiant's (now Radiant Solutions) Tomnod service uses Amazon Mechanical Turk, a crowdsourcing internet platform, to identify small objects appearing in large areas of new satellite imagery. Tomnod is heavily used for commercial and humanitarian purposes. In this presentation, you hear how Radiant Solutions uses crowdsourcing to help solve large-scale computer vision and machine learning problems. (28:44)

An Eye in the Sky: How Radiant Solutions Processes Satellite Imagery with AI and Amazon Mechanical Turk

In this video, learn how researchers at Facebook use Amazon Mechanical Turk within the ParlAI (pronounced “parlay”) framework for training and evaluating AI models to perform data collection, human training, and human evaluation. Learn how you can use this interface to gather high-quality training data to build next-generation chatbots and conversational agents. (54:40)